Kevin Kasa

I am an MASc candidate at the University of Guelph, where I am advised by Graham Taylor.

I graduated with a B.Eng in Aerospace Engineering from the Toronto Metropolitan University (previously Ryerson University). Previously, I've worked on applying machine learning to medical imaging and surgical assessment with the Orthopaedic Biomechanics Lab at the Sunnybrook Research Institute. I also spent one year working on machine learning for Geointelligence applications at MDA. In the past I've worked on research projects including robotics, orbital dynamics, synthetic aperture radar (SAR) and remote sensing, as well as at companies like IBM and Deloitte.

In addition to machine learning research, I am also very interested in deep tech entrepreneurship, having previously worked on bringing autonomous high-payload drones to the skies.

Email  /  GitHub  /  Google Scholar  /  LinkedIn

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I'm interested in computer vision and machine learning.

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Multi-Modal Deep Learning for Assessing Surgeon Technical Skill

Kevin Kasa, David Burns, Mitchell G. Goldenberg, Omar Selim, Cari Whyne, Michael Hardisty
MDPI Sensors, 2022

Multi-modal (kinematic + image) deep learning model for surgical skill assessment.

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Deep Learning for Vessel Detection and Identification from Spaceborn Optical Imagery

Giona Matasci, Jonathan Plante, Kevin Kasa, Payam Mousavi, Andrew Stewart, Andrew Macdonald, Anne Webster, Jennifer Busler
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXIV ISPRS Congress, 2021

Siamese networks for re-identifying vessels via spaceborn optical imagery. Developed an automated pipeline for collecting a large geospatial dataset (WorldView-2/3), processing, & detecting 200k+ vessels.

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A modular system for behaviour analytics from airborne full-motion video

Andrew Stewart, Fouad Faraj, Helen You, Jonathan Plante, Michael Lim, Kevin Kasa, Austin Beauchamp, Anne Webster, Leigh Martin-Boyd, Ken Wong, Alexander Braun, Andrew J. Macdonald
SPIE Defense + Commercial Sensing, 2021

Object detection + tracking from UAS video.

Design and source code from Jon Barron's website